LSU Research Bites: Tool Helps Protect Crops from Infections by Accelerating Fungal Tracking
April 09, 2026
Melanie Madrigal, a graduate student in the LSU Department of Biological Sciences who works in Jordan A. Dowell's lab, has an odd lab “pet”: a fungus known as gray mold or Botrytis cinerea.
“If you’ve ever seen mold growing on a strawberry, that’s the mold we work with,” Madrigal said.
This fungus is a highly pervasive pathogen that destroys many plants, crops, and postharvest produce. It can grow on nearly any living plant, while plants that are damaged by extreme weather, for example, are most susceptible. On the upside, it’s very easy to grow in the lab as long as the environment is warm and humid, Madrigal said.
Gray mold and other fungi spread by extending hyphae, filamentous structures that branch out and forage for nutrients. As the fungus grows, the hyphae often merge to form complex networks.
The patterns of hyphal growth are shaped by the environment in which they are growing. If nutrients are low, they grow and explore outward in a large, thin network. If there are plenty of nutrients, such as on a decaying strawberry, the hyphae form a narrower, denser network. If environmental conditions are harsh, the hyphae might even develop a form of armor or dig and bury themselves within plants for protection.
But why do Madrigal and other researchers in the field care about how fungal hyphae grow? The growth patterns can reveal a lot about how the fungi find plants to feed on and how they adapt to their environment through genetic changes that can help them evade fungicides, for example.
Studying the growth patterns of gray mold can help scientists better understand how this fungus adapts to environmental changes and responds to existing and new fungicides.
But here, things get really tricky. Studying the fungal growth network is harder than it might seem. The process is difficult and time-consuming, requiring hours of manual tracing of hyphae. It also usually requires disturbing the growing fungi, making it difficult to track dynamic growth over time.
Madrigal has been studying how gray mold hyphae grow toward or away from plant compounds that might serve as either a “I’m hurt! I’m food!” signal or a “Stay away!” signal. In the course of her research, Madrigal took thousands of photos of growing hyphal networks… but then didn’t know what to do with all of these images.
Serendipitously, another student who works in the Dowell lab, Jenna Moseley, connected Madrigal with her brother, Aaron Moseley, who had experience with image analysis and coding.
“What previously took us several hours of manual tracing of hyphae per sample, SkelPy can do in minutes.”
Melanie Madrigal, graduate student, LSU Department of Biological Sciences
Together, the group brainstormed how to extract data about the hyphal growth network through images automatically. They ended up developing a new open-source tool called SkelPy that can create “skeletonized” figures from fungal photographs, saving researchers hours of observation time.
SkelPy is a free, Python-based tool with a graphical interface that converts microscope images into simplified “skeletons” of fungal networks. It detects hyphal edges to create a network skeleton. Researchers can use it to describe the growth and shape of growing fungal hyphae over time using time-series images, without disturbing the fungal sample.
SkelPy can answer questions about how quickly the fungus is growing, and whether the hyphal network is scattered and exploratory or interconnected and dense. It can extract data from a dense hyphal network that might otherwise be very difficult for a human to trace by hand.
It quickly and automatically turns complex fungal images into measurable data. Madrigal has shown that SkelPy data can distinguish invasive, fast-growing strains of gray mold from slower, tamer ones.
“What previously took us several hours of manual tracing of hyphae per sample, SkelPy can do in minutes,” Madrigal said.
The researchers are excited for other researchers to take advantage of SkelPy, whether they study fungal growth networks or other branching systems like plant roots.
Read the study: SkelPy: A graphic user interface–based approach for skeletonizing fungal networks